{"title":"Neural manifolds: from basic science to practical improvements in brain-computer intefaces","authors":"S. Chase","doi":"10.1109/IWW-BCI.2019.8737339","DOIUrl":null,"url":null,"abstract":"Intracortical brain-computer interfaces hold the potential to improve the quality of life for patients living with motor control disorders. However, a critical barrier to the successful clinical translation of these devices is recording instability, which, if unmitigated, can quickly cause control to deteriorate. Recent findings have indicated that high-dimensional neural population activity resides in a low-dimensional “neural manifold”. Here I will introduce the concept of neural manifolds and briefly recap recent findings showing that neural manifolds constrain the types of brain-computer interface mappings that can be easily learned. Finally, I will show how these neural manifolds can be leveraged to mitigate the effects of neural recording instability, enabling stable control in the presence of even severe recording instabilities.","PeriodicalId":345970,"journal":{"name":"2019 7th International Winter Conference on Brain-Computer Interface (BCI)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 7th International Winter Conference on Brain-Computer Interface (BCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWW-BCI.2019.8737339","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Intracortical brain-computer interfaces hold the potential to improve the quality of life for patients living with motor control disorders. However, a critical barrier to the successful clinical translation of these devices is recording instability, which, if unmitigated, can quickly cause control to deteriorate. Recent findings have indicated that high-dimensional neural population activity resides in a low-dimensional “neural manifold”. Here I will introduce the concept of neural manifolds and briefly recap recent findings showing that neural manifolds constrain the types of brain-computer interface mappings that can be easily learned. Finally, I will show how these neural manifolds can be leveraged to mitigate the effects of neural recording instability, enabling stable control in the presence of even severe recording instabilities.